A Year End Update on the LIBOR Transition
Develop a machine learning model to predict future customer churn in order to develop a marketing strategy and action plan targeting your at-risk customers.
Preventing churn is key to customer satisfaction and improving customer loyalty. The challenge is to detect the customers most likely to churn based on a Machine Learning model that assigns a score representing the probability of the customer's departure from the competition.
The customers with the highest churn score can then be the object of anti-churn marketing offers in order to improve customer satisfaction and avoid leaving the competition.
The implementation of the scoring model from construction to industrialization was done in six steps:
Exploratory analysis of the marketing context and customer loyalty based on CRM data
Communication with the marketing teams in order to build the most relevant model from both a statistical and business point of view. Choice of the algorithm according to the case study and the marketing context.
Storage of the prediction model in order to facilitate the implementation in our client's IS
Collaboration with our team of marketing and customer experience consultants to build an anti churn marketing action plan based on the scoring model.
We obtain a churn prediction model with an accuracy of 85%.
The attribution of a churn score per customer allows us to reduce the targeting scope of CRM campaigns, to avoid spam, to be more relevant and efficient on the message, but also to reduce the cost of the campaigns.
The integration of the churn score in the customer advisor tools allows for better feedback to advisors on the churn risks for each customer, and thus a personalization of business practices.
Our teams of experts in Data Science and Customer Relationship Management will help you strengthen your customer relationship management and marketing strategy at every stage of the customer journey: from customer prospecting to preventing churn, increasing customer value and building loyalty. We intervene on different issues: market analysis, customer knowledge, customer segmentation. Detection of customer behaviour. Product recommendation. Analysis and improvement of customer satisfaction and service.
Our technical expertise is also complemented by a strong business knowledge thanks to our data scientists specialized in customer and marketing subjects and our Business Unit Marketing & Customer Experience, which allows us to respond to the specific issues of each of our customers.
Heka is the ecosystem of Artificial Intelligence solutions developed by Sia Partners. These advanced Data Science solutions come from years of development experience and support of our customers. Our developed industrial tools and insights allow Sia Partners to address recurring business issues and support value creation across multiple sectors.